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Merged
sfluegel05 merged 3 commits into from
Sep 19, 2025
Merged

Inference dependencies #24

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0de10c1
move inference dep to main dep
aditya0by0 Sep 2, 2025
6510f07
separate dependency for linters
aditya0by0 Sep 16, 2025
bf3335f
add descriptatorus to mandatory dependencies
sfluegel05 Sep 19, 2025
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6 changes: 3 additions & 3 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@ or install it directly with
pip install git+https://github.com/ChEB-AI/python-chebai-graph.git
```

The dependencies `torch`, `torch_geometric` and `torch-sparse` cannot be installed automatically.
The dependencies `torch`, `torch_geometric` and `torch_scatter` cannot be installed automatically.

Use the following command:

Expand All @@ -27,8 +27,8 @@ pip install torch torch_scatter torch_geometric -f https://data.pyg.org/whl/torc
```

Replace:
- `${TORCH}` with a PyTorch version (e.g., `2.6.0`; for later versions, check first if they are compatible with torch_scatter and torch_geometric)
- `${CUDA}` with e.g. `cpu`, `cu118`, or `cu121` depending on your system and CUDA version
- `${TORCH}` with a PyTorch version (e.g., `2.8.0`; for later versions, check first if they are compatible with torch_scatter and [torch_geometric](https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html))
- `${CUDA}` with `cpu`, `cu118`, `cu121` (or other, depending on your system and CUDA version)

If you already have `torch` installed, make sure that `torch_scatter` and `torch_geometric` are compatible with your
PyTorch version and are installed with the same CUDA version.
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16 changes: 8 additions & 8 deletions pyproject.toml
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Expand Up @@ -7,21 +7,21 @@ authors = [
]
dependencies = [
"chebai",
"descriptastorus"
# below packages need to manually installed as mentioned in readme
# torch-geometric
# torch_scatter
]

[project.optional-dependencies]
dev = [
"tox",
"pre-commit",
"black"
"descriptastorus",
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@sfluegel05 sfluegel05 Sep 9, 2025

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descriptastorus is needed for creating datasets, right? I would put that under dependencies (as it is not just used for development)

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@aditya0by0 aditya0by0 Sep 13, 2025

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The main dependencies should have only packages required to inference of the model. Hence, "descriptastorus" is placed under optional dependency as its not needed for inference but used during dataset creation.

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@sfluegel05 sfluegel05 Sep 15, 2025

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Then we should follow the approach from #114 and differentiate between training and linters

]

inference = [
"chebai" # pip install chebai[inference]
# below packages need to manually installed as mentioned in readme
# torch-geometric
# torch_scatter
linters = [
"isort",
"pre-commit",
"black",
]

[build-system]
Expand Down